Lead Systems Engineer; Rust - AI Platform

Lead Systems Engineer (Rust) — AI Platform

What if your deep expertise in Rust could directly shape the infrastructure powering the next generation of AI? We're looking for a senior Rust engineer to build, optimize, and lead the systems that make cutting‑edge AI research and production workflows possible — working alongside world‑class teams at leading AI labs.

This is a fully remote contract role with flexible commitment. You'll be embedded in real production environments, solving hard problems at the intersection of systems engineering and AI infrastructure.

• Organization:
  Alignerr
• Type:
  Hourly Contract
• Location:
  
  Remote
• Commitment: 20–40 hours/week

• Design, build, and optimize high‑performance systems in Rust that power AI data pipelines and evaluation workflows at scale
• Develop full‑stack tooling and backend services for large‑scale data annotation, validation, and quality control
• Own and improve reliability, performance, and safety across existing Rust codebases
• Identify bottlenecks, edge cases, and failure modes in complex systems — then implement scalable, elegant fixes
• Collaborate closely with data, research, and engineering teams to accelerate model training and evaluation
• Lead synchronous system design reviews and drive architectural decisions with clarity and confidence

• Native or fluent English speaker with strong written and verbal communication skills
• 5+ years of professional experience writing production‑grade Rust, with a focus on system architecture and API design
• Deep expertise in FFI (Foreign Function Interface) and unsafe Rust, with a strong understanding of how to manage boundaries between Rust and other languages safely
• Advanced command of asynchronous runtimes and multi‑threaded environments — you understand concurrency deeply and write code that proves it
• Confident leading system design reviews and articulating complex technical tradeoffs to cross‑functional teams
• Able to commit 20–40 hours per week with reliability and professionalism

• Prior experience with data annotation, data quality pipelines, or evaluation systems
• Familiarity with AI/ML workflows, model training, or benchmarking infrastructure
• Experience building or maintaining distributed systems or developer tooling
• Exposure to working with research teams or in fast‑moving AI environments

• Work on real, high‑impact production systems alongside some of the best AI research teams in the world
• Fully remote and flexible — structure your work around your life, not the other way around
• Freelance autonomy with the depth and significance of meaningful engineering work
• Get direct exposure to next‑generation AI infrastructure at the frontier of the field
• Potential for ongoing engagement and expanded scope as new projects launch